Build a go-to-market plan that's a stage-appropriate system — customers, channels, pricing, timing, and partnerships that fit the company's maturity — not a generic launch checklist. Gates on GTM readiness (validated demand) and company stage, picks the right channel and entry timing, and treats the buyer journey as non-linear. Catches the defaults Claude misses: GTM-as-one-time-launch, stage-skipping, channel/timing blindness, funnel-forcing, partnerships-as-shortcut. Trigger when asked to create a GTM/go-to-market plan, launch plan, channel or distribution strategy, market-entry/timing plan, or launch metrics.
Run a product-analytics analysis that produces a decision, not a dashboard — start from the question, pick actionable over vanity metrics, separate signal from noise, segment (averages lie), pair quant with qual, and end in an insight→impact→action story. Catches the defaults Claude misses: vanity metrics, correlation-as-causation, reacting to small samples/short windows, survivorship/selection bias, unsegmented averages. Trigger when asked to analyze product data/metrics, plan what to measure, build a funnel/cohort/segment/retention analysis, read analytics, or turn data into a recommendation.
Design or critique an A/B test or controlled product experiment with statistical rigor — pre-registered falsifiable hypothesis, sample-size/power up front, a full business cycle, one primary metric plus guardrails, segment + long-term reads, and a pre-set iterate/pivot/persevere decision. Catches the defaults Claude misses: peeking/early stopping, tiny samples, no guardrails, vanity metrics, "it won" with no learning loop. Trigger when asked to set up or review an A/B test, design an experiment, pick experiment metrics, decide sample size/significance/duration, or interpret/act on test results.
Run a structured rigor audit on how a team validated (or plans to validate) its assumptions — for a discovery plan, experiment, test, or any "we validated it" claim. Produces a severity-rated issue list with concrete fixes — catches testing the comfortable assumption instead of the riskiest, untestable phrasing, method fidelity mismatched to decision risk, stated intent mistaken for behavior, success criteria set after the fact, goalpost-moving, and underpowered evidence. Use when reviewing a validation/discovery approach or as the validation step after generating an assumption-test plan.
Run a structured quality audit on a product decision or its rationale — a build/buy/sunset/re-platform/pricing call, a decision log, a retrospective, or any "we decided X because…". Produces a severity-rated issue list with concrete fixes — catches outcome-based reasoning (resulting), deliberation mismatched to reversibility, uncalibrated confidence, confirmation/anchoring/framing/sunk-cost bias, missing pre-mortems, and undocumented reasoning. Use when reviewing a major decision or its write-up, or as a validation step after a decision is made.
Run a structured validity audit on OKRs, KPIs, North Star Metrics, or any success-metric set. Produces a severity-rated issue list with concrete fixes — catches vanity metrics, unfalsifiable key results, outputs disguised as outcomes, gameable targets without guardrails, and metrics disconnected from business value. Use when reviewing OKRs, goals, KPIs, dashboards, or success metrics, or as a validation step after defining metrics in a spec, roadmap, or strategy doc.
Run a structured rigor audit on prioritization decisions, scored backlogs, RICE/ICE/MoSCoW outputs, or roadmap orderings. Produces a severity-rated issue list with concrete fixes — catches invented scores with false precision, priorities unmoored from strategy, feature-factory ordering, everything-is-a-must-have inflation, and trade-offs left implicit. Use when reviewing a prioritized backlog, scoring exercise, roadmap order, or "what should we build first" decision, or as a validation step after any prioritization work.
Run a structured quality audit on a product spec, PRD, or requirements document. Produces a severity-rated issue list with concrete fixes — catches untestable requirements, happy-path-only flows, missing scope exclusions, absent dependencies/constraints/assumptions, implementation details leaking into functional specs, and unvalidated assumptions presented as facts. Use when reviewing a spec, PRD, or requirements doc, or as the validation step after writing one.